Abstract:
This work is devoted to the study and solution of the problems of modeling
complex objects on the example of the atmospheric block of the primary oil refining
unit, associated with the deficit and fuzziness of the necessary initial information. Since
many real technological objects of oil refining and other industries are often characterized
by a deficit and fuzziness of the necessary information for their study, modeling, and
optimization, this work allows solving an urgent scientific and practical problem. An
effective method has been proposed that allows, based on a system approach, expert
assessment methods, theories of fuzzy sets, and available information of various natures
to develop hybrid models of complex objects in conditions of deficiency and fuzzy initial
information. Based on the proposed hybrid method and available statistical and fuzzy
information, effective hybrid models of atmospheric block columns of the primary oil
refining unit were developed. In this case, statistical models were developed based on
experimental and statistical data. With crisp input, mode parameters, and fuzzy output
parameters, atmospheric block fuzzy models based on the proposed method, determining
the quality of the manufactured products, were developed. Moreover, with the fuzzy
input, mode, and output parameters of the atmospheric block columns, linguistic models
based on the methods of expert assessments, logical rules of conditional inference, and the
proposed method, assessing the quality of the produced gasoline, were developed. The
linguistic models developed in Fuzzy Logic Toolbox allow for the assessment of the quality
of gasoline from the atmospheric block depending on the content of chloride salts and
the mass fraction of sulfur in the raw material. The results obtained using the proposed
modeling method show their advantages in comparison with known modeling methods.
